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The objective of the article is to present an integrated True Random Number Generator (TRNG) and Physically Unclonable Function (PUF) architecture using Photovoltaic solar cells. We illustrate that the Photovoltaic (PV) solar cell sensor response can be engineered into dynamic (TRNG) and static responses (PUF). The proposed prototype uses the iterative Von Neumann post-processing scheme to produce random bits with 34% better throughput compared to a single Von Neumann operation. The random bit quality was checked by statistical test suites from the National Institute of Science and Technology (NIST) and achieves an average p-value of 0.45 at all variations in light intensity. The PUF response achieves 92.13% reliability and 50.91% uniformity. The integrated TRNG-PUF architecture is beneficial for resource-constrained Cyber-Physical System (CPS). 

We propose a method to include security and reliability to the messages sent over the CAN bus. Our approach adheres to CAN standard ISO 11898-1. A reliable PUF response is used in key generation to create a unique shared AES-256 key between each ECU, allowing for all message paths to be encrypted. In addition, an HMAC system with a counter is implemented to help protect against replay attacks and message tampering within the network. 

Internet of Things (IoT) has facilitated the connection of many smart devices via internet. Recent cyberattacks have shown that resource constrained IoT nodes are easy prey that lead towards compromising the secrecy of the data and vulnerabilities could be exploited remotely to take control of safety-critical systems. Photoresistor sensors have applications in IoT systems, such as smart street lighting, intelligent cameras, light activated smart consumer electronics, smart home, smart healthcare, etc. Building hardware security primitives, such as True Random Number Generator (TRNG), based on the intrinsic properties of photoresistor would be a novel direction to develop cost-savvy IoT security primitives. Therefore, this paper proposes a TRNG prototype that is devised from uncertainty presents in photoresistor sensors. The proposed TRNG prototype does not require any complex interfacing for preprocessing the weak signal, thereby reducing the unnecessary delay and the recurring hardware cost. The proposed prototype employs the novel approach of additive scrambling that aids to sample sensors at a higher rate. The proposed TRNG has an average random bit generation rate of 8 kbps that is better than the recent work in the literature. The quality of randomness was validated by 15 test batteries of NIST STS test. 

The last few decades have seen a large proliferation in the prevalence of cyber-physical systems. This has been especially highlighted by the explosive growth in the number of Internet of Things (IoT) devices. Unfortunately, the increasing prevalence of these devices has begun to draw the attention of malicious entities which exploit them for their own gain. What makes these devices especially attractive is the various resource constraints present in these devices that make it difficult to add standard security features. Therefore, one intriguing research direction is creating security solutions out of already present components such as sensors. Physically Unclonable Functions (PUFs) are one potential solution that use intrinsic variations of the device manufacturing process for provisioning security. In this work, we propose a novel weak PUF design using thermistor temperature sensors. Our design uses the differences in resistance variation between thermistors in response to temperature change. To generate a PUF that is reliable across a range of temperatures, we use a response-generation algorithm that helps mitigate the effects of temperature variation on the thermistors. We tested the performance of our proposed design across a range of environmental operating conditions. From this we were able to evaluate the reliability of the proposed PUF with respect to variations in temperature and humidity. We also evaluated the PUF’s uniqueness using Monte Carlo simulations. 

Internet of Things (IoT) devices are mostly small and operate wirelessly on limited battery supply, and therefore have stringent constraints on power consumption and hardware resources. Therefore, energy-efficient (low energy) design is paramount for the successful deployment of resource constrained IoT devices. Further, Physical Unclonable Functions (PUFs) have evolved as a popular hardware security primitive for low cost, mass produced IoT devices with very constrained resources. Energy harvesting technologies utilizing solar cells are being used in ultra-low power IoT devices to satisfy the energy requirement. In this paper, we utilize the intrinsic variations in solar cells to design a novel solar cell based PUF. As a proof of concept, we have used the Tiva TM4C123GH6PM microcontroller to build our solar cell based PUF. From our experiments, we found that the proposed solar cell based PUF has the uniformity value of 49.21% which is close to the ideal value of 50%. Further, the proposed solar cell based PUF has worst case reliabilities of 92.97% and 90.62% with variations in temperature and light intensity, respectively.